Long-term Inertial Navigation Accuracy Test:
The first test is to demonstrate the most important results: the pose estimation accuracy.
In this test, the processed IMU measurements by both the proposed and the traditional methods are fused respectively with only visual sensor data using the approach of [1]},
for open-loop positional estimation.
On the other hand, the EL. [2]} and TLIO [3]} methods only utilize IMU measurements.
Note that, in this test, we sought to obtain the `best possible' inertial navigation accuracy for all competing algorithms. By computing observable IMU terms, both Tr. and Pr. allow sensor fusion probabilistically. On the other hand, since EL. [2]} and TLIO [3]} directly regress for IMU's relative poses, the standard methods of fusing visual and inertial data become not applicable.
Results of VINS are the reported ones in [6]}.
